Bibliographic record
Abstract
Various global crises have intensified interest in online learning in higher education and prompted institutions to adopt innovative teaching approaches. However, the effectiveness of these online methods, particularly in disciplines such as Counselling and Ethics, remains insufficiently investigated. This reflective, evaluative study aims to examine key lessons learned from teaching Counselling and Ethics online to 60 postgraduate social work students at the University of Western Australia. The unit was designed using a blended approach that combined synchronous and asynchronous teaching methods, including pre-recorded lectures, discussion boards, and reflective journaling. This study is qualitatively informed by a social constructivist framework. A central component of this study is an evaluative inquiry addressing the research question: “How do social work students in the Counselling and Ethics unit perceive their experience of studying online at the University of Western Australia?” The 60 students enrolled in the unit were invited to evaluate the effectiveness of the pedagogical approaches employed in the module. A combination of open- and closed-ended questions was used to gather students’ perceptions. Additional sources, including performance statistics from the learning management system (LMS), reflective notes, and both formal and informal feedback, were also incorporated into the evaluative process. Most responses were positive, indicating that students were generally satisfied with the teaching quality and overall learning experience. The findings highlighted the value of peer review activities, the flexibility provided by pre-recorded lectures, and the positive impact of reflective journals on learning. These findings contribute to the existing literature on students’ perspectives of online learning, offering fresh insights for the academic community. The study also provides practical guidance for designing and delivering online or hybrid curriculum programs in counselling and ethics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".